Fix smollm2 alias to point at SmolLM2-135M (v2) instead of SmolLM-135M (v1)

[Copilot]

Summary

The original SmolLM2 PR (#9354) started as v1 support, was renamed to smollm2 during review, but the repo ID and rope_theta were never updated to v2 values. The two checkpoints are genuinely different models (0/272 tensors match).

• HUGGING_FACE_REPO_IDS["smollm2"]: HuggingFaceTB/SmolLM-135M → HuggingFaceTB/SmolLM2-135M
• examples/models/smollm2/135M_config.json: rope_theta 10000.0 → 100000.0 (matches SmolLM2-135M HF config)

Test plan

Data-only change (one string, one number). Verified values match the upstream HuggingFace SmolLM2-135M config.

[pytorch-bot]

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[Copilot]

Pull request overview

This PR corrects the smollm2 model aliasing in the LLaMA export tooling so it points to the SmolLM2 v2 checkpoint and uses the matching RoPE theta value, aligning ExecuTorch’s built-in smollm2 configuration with the upstream HuggingFace SmolLM2-135M settings.

Changes:

• Update HUGGING_FACE_REPO_IDS["smollm2"] to HuggingFaceTB/SmolLM2-135M.
• Update SmolLM2 135M example config rope_theta to 100000.0.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File	Description
examples/models/smollm2/135M_config.json	Updates RoPE theta to match SmolLM2-135M upstream config.
examples/models/llama/export_llama_lib.py	Fixes smollm2 HF repo ID used for auto-download/convert when no checkpoint is provided.

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[kirklandsign]

@claude review

[claude]

Claude finished @kirklandsign's task in 49s —— View job

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Review of PR #18859

• Read changed files and diff
• Verify changes against upstream HuggingFace config
• Post review feedback

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LGTM. This is a straightforward data-only fix and the changes are correct.

I verified both values against the upstream HuggingFace configs:

Field	Before (SmolLM v1)	After (SmolLM2 v2)	Upstream SmolLM2-135M
Repo ID	HuggingFaceTB/SmolLM-135M	HuggingFaceTB/SmolLM2-135M	✅ matches
rope_theta	10000.0	100000.0	✅ matches

All other config values in 135M_config.json (dim: 576, n_heads: 9, n_kv_heads: 3, n_layers: 30, vocab_size: 49152, etc.) already match the upstream SmolLM2-135M config, so no further changes are needed.

No issues found.

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